Fusion-acquisition

Résumé

L’expression fusion-acquisition ou fusions et acquisitions (parfois aussi appelée « Fusac », ou en anglais M&A, un acronyme pour mergers and acquisitions) signifie le regroupement d'entreprises et recouvre les différents aspects du rachat du capital d'une entreprise, d'une division d'entreprise, voire d'actifs, par une autre entreprise. Chaque opération est une transaction habituellement majoritaire, ce qui signifie qu'elle entraîne un échange financier entre un ou plusieurs vendeurs et un acheteur et une modification des droits de propriété de la cible. On distingue une opération de reclassement de capital d'une opération de M&A, lorsqu'une partie minoritaire du capital d'une entreprise est cédée d'un actionnaire à un autre sans entraîner de changements notables dans son management. Dans ce dernier cas, il s'agit essentiellement d'investissement financier plus qu'industriel mais la limite entre les deux peut parfois être ténue sur une longue période.

Source officielle

https://fr.wikipedia.org/wiki/Fusion-acquisition

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Essays in Financial Economics

Kevin Marc Rageth

This thesis consists of two chapters that study separate subjects in the area of corporate finance.The first chapter, titled âEconomic Gains in Bank Mergers and Acquisitions â Evidence from Targetsâ, investigates economic gains in bank mergers and acquisitions (M&A) by focusing on bank targets. Demonstrating efficiency increases resulting from bank M&A has been elusive to the banking literature. Imake use of a novel hand-collected dataset, which allows to observe financial statements for transacted target banks both before and after the deal effective date. Addressing endogeneity concerns by constructing the counterfactual frommergers that fail for reasons exogenous to target performance, I show evidence that acquiring banks create economic value by pursuing M&A deals. Cost reductions and higher post-deal securities productivity constitute bankM&A related value sources. The results are consistent with banks pursuingM&A to realize economies of scale.The second chapter, which is co-authored work with RÃŒdiger Fahlenbrach and RenÃ© Stulz, is titled âHow Valuable Is Financial Flexibility when Revenue Stops? Evidence from the COVID-19 Crisisâ. We use the COVID-19 shock as a laboratory to investigate the value of financial flexibility. Firms with greater financial flexibility should be better able to fund a revenue shortfall resulting from the COVID-19 shock and benefit less from policy responses. We find that firms with high financial flexibility within an industry experience a stock price drop that is 26%, or 9.7 percentage points, lower than those with low financial flexibility. This differential return persists as stock prices rebound. Firms more exposed to the COVID-19 shock benefit more from cash holdings. No evidence suggests that recent payouts worsened the average firmâs drop in stock price. Our results cannot be explained by a leverage effect.

EPFL2022

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I started my Ph.D. studies in the Fall 2008, a period ex-post perceived as being at the core of the Financial Crisis. At that time my ideas were vague and I struggled to find a good research topic. As surprising as it might appear, in one single week the discussions I had with my relatives provided me with enough ideas needed to write my thesis. Indeed, during that single week my relatives contacted me and complained about the fact that they had lost money invested in the financial market. They wanted me to advise them. I simply told them to invest their money in relatively safe bonds. My relatives did not realize how fruitful their behavior was for me. Indeed, after having advised them I wondered whether their willingness to gather information in bad times was optimal or pure irrationality. This issue is addressed in the first chapter of my thesis. The last two chapters investigate the impact of the willingness to gather more information in bad times than in good times on the dynamics of asset prices. My thesis answers two very important questions: When should investors acquire information given that information-processing is costly and what is the impact of the optimal information acquisition strategy on asset price dynamics? Consequently, the main topic of my thesis is the transmission of acquired information in financial markets. In the first chapter I consider a dynamic portfolio choice and costly information acquisition problem. Consistent with my relatives behavior, I show that it is optimal to gather more information in bad times than in good times. As the state of the economy worsens, investors optimally re-balance their portfolio towards safer investment and spend more and more money to gather more and more accurate information regarding future market moves. This result derived in a purely rational setup helps to understand the empirical observation that people tend to pay fluctuating attention to news, focusing more in downturns than in upturns. To the best of my knowledge, this paper is the first to consider costly information acquisition in a dynamic setting. The main contribution is to provide insights on how investors should optimally allocate their wealth to the financial market on the one hand and to information market on the other hand given current market conditions. In the second chapter (with Daniel Andrei) we model the optimal information acquisition strategy obtained in the first chapter in a general equilibrium framework and we show that this strategy (fluctuating attention paid to news) has very interesting implications on the dynamics of asset prices. Our main contribution is to highlight a J-shaped relationship between attention and volatility. By constructing an empirical measure of attention to news, we show that the theoretical prediction of our model holds in the data. Moreover, we are the first to provide a theoretical foundation for the fact that the slope of the term structure of equity premia is pro-cyclical. In the third chapter I investigate the impact of fluctuating attention to news in a multi-asset general equilibrium framework. My main contribution is to show that fluctuating attention to news generates return and volatility spillover effects among financial markets. As a bad shock hits one market, investors raise their attention to that particular market. This implies a simultaneous increase in each market volatility and in each cross-market correlation, a phenomenon called financial contagion. Moreover, I document that the interconnection between attention and uncertainty generates persistence in cross-market correlations. This very interesting result proves that persistence can be generated through Bayesian learning. Finally, I am the first to provide a theoretical foundation for the observed shape of the term structure of correlation. Consistent with empirical findings, I show that fluctuating attention implies an upward sloping term structure of correlation where the shorthand is wider than the longhand.

EPFL2013

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Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: Acquisition, calibration and validation issues

Marie Auberson, Simon Baechler, Thibault Genessay, Luc Patiny, Michaël Giuseppe Zasso

Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II). (C) 2016 Elsevier Ireland Ltd. All rights reserved.

Elsevier Ireland Ltd2016

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EPFL2013

Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: Acquisition, calibration and validation issues

Marie Auberson, Simon Baechler, Thibault Genessay, Luc Patiny, Michaël Giuseppe Zasso

Elsevier Ireland Ltd2016